Chen, Yen Jung, Wei-Cheng Tung, Wei-Rui Lee, Brijesh Patel, Vytautas Bučinskas, Modris Greitans, and Po Ting Lin. Designing and Controlling a Self-Balancing Platform Mechanism Based on 3-RCC Spherical Parallel Manipulator. Robotic Systems and Applications, 3(1), 1-16 pp. Extrica, 2023.

Bibtex citāts:
author = {Chen and Yen Jung and Wei-Cheng Tung and Wei-Rui Lee and Brijesh Patel and Vytautas Bučinskas and Modris Greitans and and Po Ting Lin},
title = {Designing and Controlling a Self-Balancing Platform Mechanism Based on 3-RCC Spherical Parallel Manipulator},
journal = {Robotic Systems and Applications},
volume = {3},
issue = {1},
pages = {1-16},
publisher = {Extrica},
year = {2023}

Anotācija: Motion control platforms have various applications in the manufacturing and automation industries. Different literature provides multiple issues related to the kinematics and dynamics of self-guided robots for transportation regarding platform balancing. Self-balancing platforms are utilized in many deliveries, stabilization, and transportation systems, and they are especially well suited for outdoor activities when the ground surface is not flat or structured. This paper describes developing a control technique for a self-balancing platform using the 3-RCC spherical parallel manipulator. This mechanism was designed to support an AGV (Automated Guided Vehicle) for transporting and lifting heavy weights for industrial applications. The AGV carries a robotic arm on top for different tasks. When the AGV encounters a steep slope or a rough surface, the AGV tilts, and the robotic arm’s performance is significantly affected. So, this study gives a solution to avoid these circumstances with a novel approach for the platform’s self-balancing mechanism consisting of a 3-RCC spherical parallel manipulator. Real-time stabilization and kinematics analysis methods are used to achieve the self-balancing system of the platform. When both methods are observed through different tilting angles for automation stability, Kinematic analysis performs more efficiently with less time duration when compared with the real-time stabilization method.